dbmazz vs LinkedIn Databus
dbmazz
github.comLinkedIn Databus
github.comSide by side
| Figure | dbmazz | LinkedIn Databus |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| macOS | Yes | — |
| Linux | Yes | — |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 1 |
| Spec score · Change Data Capture Software | 8.0 (#9) | 8.2 (#7) |
| Intended users | The README describes dbmazz as an option for teams seeking streaming PostgreSQL CDC without operating a streaming platform. | The project describes use in data architectures that route primary database changes to derived stores such as indexes, caches, and read replicas. |
| License | dbmazz uses Elastic License 2.0, which the README describes as allowing commercial and non-commercial use while restricting offering it to third parties as a managed service. | The repository identifies Databus as licensed under Apache 2.0. |
Plans
In their own words
dbmazz
dbmazz is a Rust daemon for moving database changes into a sink. It reads PostgreSQL changes through logical replication and streams inserts, updates, and deletes. The project lists PostgreSQL and MySQL as sources, and StarRocks, PostgreSQL, and Snowflake as stable sinks; S3/Iceberg is planned. Each instance handles one replication job. The project reports sub-second replication lag and about 11 MB of resident memory per daemon. Teams can try its ez-cdc CLI quickstart or run the daemon from the official Docker image. The CLI supports Linux and macOS on amd64 and arm64. Listed observability tools include Prometheus metrics, gRPC reflection, an HTTP control plane, and a live terminal dashboard. Automatic setup can create publications, replication slots, sink tables, and audit columns. Self-hosting is free; BYOC is also listed at free in a customer's AWS or GCP account, while support and optional PrivateLink cost extra. The Elastic License 2.0 permits commercial and non-commercial use but restricts offering the software to third parties as a managed service.
LinkedIn Databus
LinkedIn Databus is a self-hosted, source-agnostic distributed change data capture system. It captures and transports changes to primary data so downstream systems can process them. Relays serve change events, clients process them, and bootstrap servers supply historical events for consumers catching up. Consumers can begin at an arbitrary point in the stream, use full-data bootstrap, and consume partitions while preserving source consistency.
The project describes in-order, at-least-once delivery with high availability, low-millisecond transport latency, and throughput of thousands of events per second per server. It supports Oracle sources and has been used for search and social-graph indexes and member-profile read replicas. The wiki documents a MySQL adapter as a proof of concept, not a LinkedIn production deployment. Databus is free, licensed under Apache 2.0, and available for self-hosting. Building it requires Gradle 1.0 or later and Oracle's ojdbc6 driver version 11.2.0.2.0, which is obtained under the Oracle Technology Network License. The repository points to a wiki for documentation and examples; it does not state a support service.